{"id":"W2130344546","doi":"10.1145/1181775.1181777","title":"Using task context to improve programmer productivity","year":2006,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":447,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Programmer; Computer science; Task (project management); Context (archaeology); Human–computer interaction; Task switching; Task management; Task analysis; Software engineering; Programming language; Systems engineering; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005027579,0.0005617177,0.0004645751,0.001599025,0.0008951256,0.002134683,0.0008120554,0.0007225543,0.001537121],"category_scores_gemma":[0.045585,0.0004095126,0.000417885,0.0009335753,0.0005290035,0.002743376,0.002168424,0.000686879,0.000402433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000660427,"about_ca_system_score_gemma":0.001697084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002371377,"about_ca_topic_score_gemma":0.003713833,"domain_scores_codex":[0.9950483,0.002754184,0.0002759364,0.0006360069,0.0009884988,0.0002970589],"domain_scores_gemma":[0.9687262,0.0184707,0.004263112,0.004751013,0.002279161,0.001509813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001119462,0.001651956,0.1678364,0.0006455542,0.000144667,0.0002492685,0.009042477,0.00775632,0.02332004,0.006161038,0.006812762,0.7752601],"study_design_scores_gemma":[0.00104889,0.007334387,0.6116959,0.0009046085,0.00104377,0.001614229,0.01296629,0.1715698,0.04597275,0.06274844,0.08235516,0.0007459026],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8751929,0.001225786,0.109658,0.001478831,0.00009906882,0.0002199752,0.0001800405,0.002274927,0.00967036],"genre_scores_gemma":[0.9464891,0.0002220941,0.05195558,0.0001753966,0.0000475606,0.000129496,0.0001243014,0.0000783537,0.00077807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005027579,"threshold_uncertainty_score":0.02658868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3139545480922422,"score_gpt":0.4520012210452668,"score_spread":0.1380466729530246,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}